Adaptive Interim Analyses in Clinical Trials

In long-term experiments, it is natural to wish to examine the data as they accumulate instead of waiting until the conclusion. However it is clear that, with frequent looks at the data, there is an increased probability of seeing spurious results and making a premature and erroneous decision. To overcome this danger of overinterpretation of interim results, special statistical analysis methods are required. To address this need, the first classic books on sequential analysis were published by Wald (1947), motivated primarily by quality control applications, and by Armitage (1960) for medical trials. In this chapter, we shall be concerned with the latter application. The benefits of monitoring data in clinical trials are obvious: Administrative. One can check on accrual, eligibility, and compliance, and generally ensure the trial is being carried out as per protocol.